Scientists at the University of Bristol have shown that reinforcement learning, a type of machine learning in which a computer program learns to make decisions by trying different actions, significantly outperforms commercial blood glucose controllers in terms of safety and effectiveness. By using offline reinforcement learning, where the algorithm learns from patient records, the researchers improve on prior work, showing that good blood glucose control can be achieved by learning from the decisions of the patient rather than by trial and error.
‘Offline Reinforcement Learning for Safer Blood Glucose Control in People with Type 1 Diabetes’ by Harry Emerson et al. in Journal of Biomedical Informatics.